1. Field
This disclosure relates generally to workflows and, more particularly, to training or quality control systems for workflows.
2. Description of the Related Art
Many kinds of industries, businesses, and applications use software systems that manage the flow, progress, rate, or amount of work or data (the “workflow”) to and from an office, department, employee, individual, or group of individuals. Healthcare providers such as hospitals use workflow systems like Clinical Information Systems (CIS) and/or Hospital Information Systems (HIS) to manage administrative, financial, medical, and/or laboratory data; Radiology Information Systems (RIS) to store, manipulate, and distribute patient radiological data and imagery; and Picture Archiving and Communication Systems (PACS) for managing medical imaging aspects of the workflow.
Workflows can be used to increase productivity. For example, a primary care physician can recommend that a sick patient have a medical image captured in order to facilitate diagnosis. An MRI acquires the image, and the image is sent to a PACS server. A clinician who specializes in making diagnoses from MRI can access the sick patient's image stored on the PACS system through a diagnostic review workstation. The clinician evaluates the image and makes a diagnosis based on the image, entering the normal or abnormal diagnosis into the workstation's interface. The sick patient's diagnosis is transmitted to a CIS. The primary care physician can later query the CIS and view the diagnostic clinician's diagnosis. The physician presents this diagnosis to the patient. Because the acts of judging the image and making the diagnosis are moved from the primary-care physician to the diagnosing clinician, the primary-care physician has more time to visit with other patients. Furthermore, the diagnosing clinician can efficiently review large numbers of images in series without having to visit with patients. PACS thus increases both the physician's and the diagnosing clinician's productivity.
Although workflows such as CIS, HIS, RIS, PACS, and others can increase productivity and can efficiently store and present data, these workflows have significant drawbacks. Serial workflows, like the diagnosing clinician's workflow described above, typically present a preponderance of normal data and only a very small percentage of abnormal data. This gives rise to a tendency to under-identify abnormal data in a workflow, particularly if the workflow is presented at a rapid pace. For example, a diagnosing clinician can use PACS to review long series of radiological images and diagnose health conditions. Most of the images presented to the diagnosing clinician show normal results. Only a small number of images typically contain abnormalities. After reviewing long series of normal data, however, the diagnosing clinician can become bored, complacent, or fatigued and may tend to under-diagnose, over-diagnose, or misdiagnose subtle and perhaps even startling abnormalities presented in the workflow.